Orthogonal transform generation with subspace constraint

ABSTRACT

This disclosure relates to a transform kernel sharing in video encoding and decoding. For example, a method is disclosed for such transform kernel sharing. The method may include identifying a plurality of transform kernels, wherein each of the plurality of transform kernels comprises a set of basis vectors from low to high frequencies; N high-frequency basis vectors of two or more of the plurality of transform kernels are shared, N being a positive integer; and low-frequency basis vectors of the two or more of the plurality of the transform kernels other than the N high-frequency basis vectors are individualized. The method may further include extracting a data block from a video bitstream; selecting a transform kernel from the plurality of transform kernels based on information associated with the data block; and applying the transform kernel to at least a portion of the data block to generate a transformed block.

INCORPORATION BY REFERENCE

This application is based on and claims the benefit of priority to U.S.Provisional Application No. 63/172,060, entitled “ORTHOGONAL TRANSFORMGENERATION WITH SUBSPACE CONSTRAINT”, filed on Apr. 7, 2021, which isherein incorporated by reference in its entirety.

TECHNICAL FIELD

This disclosure describes a set of advanced video coding technologies.More specifically, the disclosed technology involves a transform kernelsharing method in video encoding and decoding.

BACKGROUND

This background description provided herein is for the purpose ofgenerally presenting the context of the disclosure. Work of thepresently named inventors, to the extent the work is described in thisbackground section, as well as aspects of the description that may nototherwise qualify as prior art at the time of filing of thisapplication, are neither expressly nor impliedly admitted as prior artagainst the present disclosure.

Video coding and decoding can be performed using inter-pictureprediction with motion compensation. Uncompressed digital video caninclude a series of pictures, with each picture having a spatialdimension of, for example, 1920×1080 luminance samples and associatedfull or subsampled chrominance samples. The series of pictures can havea fixed or variable picture rate (alternatively referred to as framerate) of, for example, 60 pictures per second or 60 frames per second.Uncompressed video has specific bitrate requirements for streaming ordata processing. For example, video with a pixel resolution of1920×1080, a frame rate of 60 frames/second, and a chroma subsampling of4:2:0 at 8 bit per pixel per color channel requires close to 1.5 Gbit/sbandwidth. An hour of such video requires more than 600 GBytes ofstorage space.

One purpose of video coding and decoding can be the reduction ofredundancy in the uncompressed input video signal, through compression.Compression can help reduce the aforementioned bandwidth and/or storagespace requirements, in some cases, by two orders of magnitude or more.Both lossless compression and lossy compression, as well as acombination thereof can be employed. Lossless compression refers totechniques where an exact copy of the original signal can bereconstructed from the compressed original signal via a decodingprocess. Lossy compression refers to coding/decoding process whereoriginal video information is not fully retained during coding and notfully recoverable during decoding. When using lossy compression, thereconstructed signal may not be identical to the original signal, butthe distortion between original and reconstructed signals is made smallenough to render the reconstructed signal useful for the intendedapplication albeit some information loss. In the case of video, lossycompression is widely employed in many applications. The amount oftolerable distortion depends on the application. For example, users ofcertain consumer video streaming applications may tolerate higherdistortion than users of cinematic or television broadcastingapplications. The compression ratio achievable by a particular codingalgorithm can be selected or adjusted to reflect various distortiontolerance: higher tolerable distortion generally allows for codingalgorithms that yield higher losses and higher compression ratios.

A video encoder and decoder can utilize techniques from several broadcategories and steps, including, for example, motion compensation,Fourier transform, quantization, and entropy coding.

Video codec technologies can include techniques known as intra coding.In intra coding, sample values are represented without reference tosamples or other data from previously reconstructed reference pictures.In some video codecs, a picture is spatially subdivided into blocks ofsamples. When all blocks of samples are coded in intra mode, thatpicture can be referred to as an intra picture. Intra pictures and theirderivatives such as independent decoder refresh pictures, can be used toreset the decoder state and can, therefore, be used as the first picturein a coded video bitstream and a video session, or as a still image. Thesamples of a block after intra prediction can then be subject to atransform into frequency domain, and the transform coefficients sogenerated can be quantized before entropy coding. Intra predictionrepresents a technique that minimizes sample values in the pre-transformdomain. In some cases, the smaller the DC value after a transform is,and the smaller the AC coefficients are, the fewer the bits that arerequired at a given quantization step size to represent the block afterentropy coding.

Traditional intra coding such as that known from, for example, MPEG-2generation coding technologies, does not use intra prediction. However,some newer video compression technologies include techniques thatattempt coding/decoding of blocks based on, for example, surroundingsample data and/or metadata that are obtained during the encoding and/ordecoding of spatially neighboring, and that precede in decoding orderthe blocks of data being intra coded or decoded. Such techniques arehenceforth called “intra prediction” techniques. Note that in at leastsome cases, intra prediction uses reference data only from the currentpicture under reconstruction and not from other reference pictures.

There can be many different forms of intra prediction. When more thanone of such techniques are available in a given video coding technology,the technique in use can be referred to as an intra prediction mode. Oneor more intra prediction modes may be provided in a particular codec. Incertain cases, modes can have submodes and/or may be associated withvarious parameters, and mode/submode information and intra codingparameters for blocks of video can be coded individually or collectivelyincluded in mode codewords. Which codeword to use for a given mode,submode, and/or parameter combination can have an impact in the codingefficiency gain through intra prediction, and so can the entropy codingtechnology used to translate the codewords into a bitstream.

A certain mode of intra prediction was introduced with H.264, refined inH.265, and further refined in newer coding technologies such as jointexploration model (JEM), versatile video coding (VVC), and benchmark set(BMS). Generally, for intra prediction, a predictor block can be formedusing neighboring sample values that have become available. For example,available values of particular set of neighboring samples along certaindirection and/or lines may be copied into the predictor block. Areference to the direction in use can be coded in the bitstream or mayitself be predicted.

Referring to FIG. 1A, depicted in the lower right is a subset of ninepredictor directions specified in H.265's 33 possible intra predictordirections (corresponding to the 33 angular modes of the 35 intra modesspecified in H.265). The point where the arrows converge (101)represents the sample being predicted. The arrows represent thedirection from which neighboring samples are used to predict the sampleat 101. For example, arrow (102) indicates that sample (101) ispredicted from a neighboring sample or samples to the upper right, at a45 degree angle from the horizontal direction. Similarly, arrow (103)indicates that sample (101) is predicted from a neighboring sample orsamples to the lower left of sample (101), in a 22.5 degree angle fromthe horizontal direction.

Still referring to FIG. 1A, on the top left there is depicted a squareblock (104) of 4×4 samples (indicated by a dashed, boldface line). Thesquare block (104) includes 16 samples, each labelled with an “5”, itsposition in the Y dimension (e.g., row index) and its position in the Xdimension (e.g., column index). For example, sample S21 is the secondsample in the Y dimension (from the top) and the first (from the left)sample in the X dimension. Similarly, sample S44 is the fourth sample inblock (104) in both the Y and X dimensions. As the block is 4×4 samplesin size, S44 is at the bottom right. Further shown are example referencesamples that follow a similar numbering scheme. A reference sample islabelled with an R, its Y position (e.g., row index) and X position(column index) relative to block (104). In both H.264 and H.265,prediction samples adjacently neighboring the block under reconstructionare used.

Intra picture prediction of block 104 may begin by copying referencesample values from the neighboring samples according to a signaledprediction direction. For example, assuming that the coded videobitstream includes signaling that, for this block 104, indicates aprediction direction of arrow (102)—that is, samples are predicted froma prediction sample or samples to the upper right, at a 45-degree anglefrom the horizontal direction. In such a case, samples S41, S32, S23,and S14 are predicted from the same reference sample R05. Sample S44 isthen predicted from reference sample R08.

In certain cases, the values of multiple reference samples may becombined, for example through interpolation, in order to calculate areference sample; especially when the directions are not evenlydivisible by 45 degrees.

The number of possible directions has increased as video codingtechnology has continued to develop. In H.264 (year 2003), for example,nine different direction are available for intra prediction. Thatincreased to 33 in H.265 (year 2013), and JEM/VVC/BMS, at the time ofthis disclosure, can support up to 65 directions. Experimental studieshave been conducted to help identify the most suitable intra predictiondirections, and certain techniques in the entropy coding may be used toencode those most suitable directions in a small number of bits,accepting a certain bit penalty for directions. Further, the directionsthemselves can sometimes be predicted from neighboring directions usedin the intra prediction of the neighboring blocks that have beendecoded.

FIG. 1B shows a schematic (180) that depicts 65 intra predictiondirections according to JEM to illustrate the increasing number ofprediction directions in various encoding technologies developed overtime.

The manner for mapping of bits representing intra prediction directionsto the prediction directions in the coded video bitstream may vary fromvideo coding technology to video coding technology; and can range, forexample, from simple direct mappings of prediction direction to intraprediction mode, to codewords, to complex adaptive schemes involvingmost probable modes, and similar techniques. In all cases, however,there can be certain directions for intro prediction that arestatistically less likely to occur in video content than certain otherdirections. As the goal of video compression is the reduction ofredundancy, those less likely directions will, in a well-designed videocoding technology, may be represented by a larger number of bits thanmore likely directions.

Inter picture prediction, or inter prediction may be based on motioncompensation. In motion compensation, sample data from a previouslyreconstructed picture or part thereof (reference picture), after beingspatially shifted in a direction indicated by a motion vector (MVhenceforth), may be used for a prediction of a newly reconstructedpicture or picture part (e.g., a block). In some cases, the referencepicture can be the same as the picture currently under reconstruction.MVs may have two dimensions X and Y, or three dimensions, with the thirddimension being an indication of the reference picture in use (akin to atime dimension).

In some video compression techniques, a current MV applicable to acertain area of sample data can be predicted from other MVs, for examplefrom those other MVs that are related to other areas of the sample datathat are spatially adjacent to the area under reconstruction and precedethe current MV in decoding order. Doing so can substantially reduce theoverall amount of data required for coding the MVs by relying onremoving redundancy in correlated MVs, thereby increasing compressionefficiency. MV prediction can work effectively, for example, becausewhen coding an input video signal derived from a camera (known asnatural video) there is a statistical likelihood that areas larger thanthe area to which a single MV is applicable move in a similar directionin the video sequence and, therefore, can in some cases be predictedusing a similar motion vector derived from MVs of neighboring area. Thatresults in the actual MV for a given area to be similar or identical tothe MV predicted from the surrounding MVs. Such an MV in turn may berepresented, after entropy coding, in a smaller number of bits than whatwould be used if the MV is coded directly rather than predicted from theneighboring MV(s). In some cases, MV prediction can be an example oflossless compression of a signal (namely: the MVs) derived from theoriginal signal (namely: the sample stream). In other cases, MVprediction itself can be lossy, for example because of rounding errorswhen calculating a predictor from several surrounding MVs.

Various MV prediction mechanisms are described in H.265/HEVC (ITU-T Rec.H.265, “High Efficiency Video Coding”, December 2016). Out of the manyMV prediction mechanisms that H.265 specifies, described below is atechnique henceforth referred to as “spatial merge”.

Specifically, referring to FIG. 2 , a current block (201) comprisessamples that have been found by the encoder during the motion searchprocess to be predictable from a previous block of the same size thathas been spatially shifted. Instead of coding that MV directly, the MVcan be derived from metadata associated with one or more referencepictures, for example from the most recent (in decoding order) referencepicture, using the MV associated with either one of five surroundingsamples, denoted A0, A1, and B0, B1, B2 (202 through 206, respectively).In H.265, the MV prediction can use predictors from the same referencepicture that the neighboring block uses.

SUMMARY

Aspects of the disclosure provide methods and apparatuses for transformkernel sharing in video encoding and decoding.

In some implementations, a method is disclosed for such transform kernelsharing. The method may include identifying a plurality of transformkernels, wherein each of the plurality of transform kernels comprises aset of basis vectors from low to high frequencies; N high-frequencybasis vectors of two or more of the plurality of transform kernels areshared, N being a positive integer; and low-frequency basis vectors ofthe two or more of the plurality of the transform kernels other than theN high-frequency basis vectors are individualized. The method mayfurther include extracting a data block from a video bitstream;selecting a transform kernel from the plurality of transform kernelsbased on information associated with the data block; and applying thetransform kernel to at least a portion of the data block to generate atransformed block.

In the implementations above, the plurality of transform kernels may bepre-trained offline. In some further implementations, the plurality oftransform kernels may be jointly trained offline to determine the Nhigh-frequency basis vector being shared.

In any of the implementations above, the N high-frequency basis vectorsmay include basis vectors with frequencies higher than a predeterminedthreshold frequency. In some further implementations, the plurality oftransform kernels and the predetermined threshold frequency may bepre-trained offline.

In any of the implementations above, the plurality of transform kernelsmay include secondary transform kernels applicable to transformingprimary transform coefficients, and the data block comprises an array ofprimary transform coefficients.

In any of the implementations above, the two or more of the plurality oftransform kernels sharing the N high-frequency basis vectors correspondto a same one of a plurality of intra-picture prediction modes; and alltransform kernels among the plurality of the transform kernels assignedto the same one of the plurality of intra-picture prediction modes sharethe N high-frequency basis vectors with other low-frequency basisvectors being individualized.

In any of the implementations above, the two or more of the plurality oftransform kernels sharing the N high-frequency basis vectors may beassigned to two or more different intra-picture prediction modes.

In any of the implementations above, the plurality of transform kernelsare secondary transform kernels; and the two or more of the plurality oftransform kernels sharing the N high-frequency basis vector areconfigured to transform primary transform coefficients generated fromprimary transforms having a same transform type.

In any of the implementations above, N is an integer power of 2, and/orN is smaller than a predefined upper bound, and/or N depends on atransform size.

In any of the implementations above, the plurality of transform kernelsmay be configured for intra secondary transform (IST). In someimplementations, the plurality of transform kernels may be secondary lowfrequency non-separable transform (LFNST) kernels. In someimplementations, the plurality of transform kernels are configured forline graph transform (LGT).

In some other implementations, a device for processing video informationis disclosed. The device may include a circuitry configured to performany one of the method implementations above.

Aspects of the disclosure also provide non-transitory computer-readablemediums storing instructions which when executed by a computer for videodecoding and/or encoding cause the computer to perform the methods forvideo decoding and/or encoding.

BRIEF DESCRIPTION OF THE DRAWINGS

Further features, the nature, and various advantages of the disclosedsubject matter will be more apparent from the following detaileddescription and the accompanying drawings in which:

FIG. 1A shows a schematic illustration of an exemplary subset of intraprediction directional modes.

FIG. 1B shows an illustration of exemplary intra prediction directions.

FIG. 2 shows a schematic illustration of a current block and itssurrounding spatial merge candidates for motion vector prediction in oneexample.

FIG. 3 shows a schematic illustration of a simplified block diagram of acommunication system (300) in accordance with an example embodiment.

FIG. 4 shows a schematic illustration of a simplified block diagram of acommunication system (400) in accordance with an example embodiment.

FIG. 5 shows a schematic illustration of a simplified block diagram of avideo decoder in accordance with an example embodiment.

FIG. 6 shows a schematic illustration of a simplified block diagram of avideo encoder in accordance with an example embodiment.

FIG. 7 shows a block diagram of a video encoder in accordance withanother example embodiment.

FIG. 8 shows a block diagram of a video decoder in accordance withanother example embodiment.

FIG. 9 shows directional intra prediction modes according to exampleembodiments of the disclosure.

FIG. 10 shows non-directional intra prediction modes according toexample embodiments of the disclosure.

FIG. 11 shows recursive intra prediction modes according to exampleembodiments of the disclosure.

FIG. 12 shows transform block partitioning and scan of an intraprediction block according to example embodiments of the disclosure.

FIG. 13 shows transform block partitioning and scan of an interprediction block according to example embodiments of the disclosure.

FIG. 14 shows low frequency non-separable transform process according toexample embodiments of the disclosure.

FIG. 15 shows sharing of high frequency basis vector between differenttransform kernels according to example embodiments of the disclosure.

FIG. 16 shows a flow chart according to example embodiments of thedisclosure.

FIG. 17 shows a schematic illustration of a computer system inaccordance with example embodiments of the disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

FIG. 3 illustrates a simplified block diagram of a communication system(300) according to an embodiment of the present disclosure. Thecommunication system (300) includes a plurality of terminal devices thatcan communicate with each other, via, for example, a network (350). Forexample, the communication system (300) includes a first pair ofterminal devices (310) and (320) interconnected via the network (350).In the example of FIG. 3 , the first pair of terminal devices (310) and(320) may perform unidirectional transmission of data. For example, theterminal device (310) may code video data (e.g., of a stream of videopictures that are captured by the terminal device (310)) fortransmission to the other terminal device (320) via the network (350).The encoded video data can be transmitted in the form of one or morecoded video bitstreams. The terminal device (320) may receive the codedvideo data from the network (350), decode the coded video data torecover the video pictures and display the video pictures according tothe recovered video data. Unidirectional data transmission may beimplemented in media serving applications and the like.

In another example, the communication system (300) includes a secondpair of terminal devices (330) and (340) that perform bidirectionaltransmission of coded video data that may be implemented, for example,during a videoconferencing application. For bidirectional transmissionof data, in an example, each terminal device of the terminal devices(330) and (340) may code video data (e.g., of a stream of video picturesthat are captured by the terminal device) for transmission to the otherterminal device of the terminal devices (330) and (340) via the network(350). Each terminal device of the terminal devices (330) and (340) alsomay receive the coded video data transmitted by the other terminaldevice of the terminal devices (330) and (340), and may decode the codedvideo data to recover the video pictures and may display the videopictures at an accessible display device according to the recoveredvideo data.

In the example of FIG. 3 , the terminal devices (310), (320), (330) and(340) may be implemented as servers, personal computers and smart phonesbut the applicability of the underlying principles of the presentdisclosure may not be so limited. Embodiments of the present disclosuremay be implemented in desktop computers, laptop computers, tabletcomputers, media players, wearable computers, dedicated videoconferencing equipment, and/or the like. The network (350) representsany number or types of networks that convey coded video data among theterminal devices (310), (320), (330) and (340), including for examplewireline (wired) and/or wireless communication networks. Thecommunication network (350) may exchange data in circuit-switched,packet-switched, and/or other types of channels. Representative networksinclude telecommunications networks, local area networks, wide areanetworks and/or the Internet. For the purposes of the presentdiscussion, the architecture and topology of the network (350) may beimmaterial to the operation of the present disclosure unless explicitlyexplained herein.

FIG. 4 illustrates, as an example for an application for the disclosedsubject matter, a placement of a video encoder and a video decoder in avideo streaming environment. The disclosed subject matter may be equallyapplicable to other video applications, including, for example, videoconferencing, digital TV broadcasting, gaming, virtual reality, storageof compressed video on digital media including CD, DVD, memory stick andthe like, and so on.

A video streaming system may include a video capture subsystem (413)that can include a video source (401), e.g., a digital camera, forcreating a stream of video pictures or images (402) that areuncompressed. In an example, the stream of video pictures (402) includessamples that are recorded by a digital camera of the video source 401.The stream of video pictures (402), depicted as a bold line to emphasizea high data volume when compared to encoded video data (404) (or codedvideo bitstreams), can be processed by an electronic device (420) thatincludes a video encoder (403) coupled to the video source (401). Thevideo encoder (403) can include hardware, software, or a combinationthereof to enable or implement aspects of the disclosed subject matteras described in more detail below. The encoded video data (404) (orencoded video bitstream (404)), depicted as a thin line to emphasize alower data volume when compared to the stream of uncompressed videopictures (402), can be stored on a streaming server (405) for future useor directly to downstream video devices (not shown). One or morestreaming client subsystems, such as client subsystems (406) and (408)in FIG. 4 can access the streaming server (405) to retrieve copies (407)and (409) of the encoded video data (404). A client subsystem (406) caninclude a video decoder (410), for example, in an electronic device(430). The video decoder (410) decodes the incoming copy (407) of theencoded video data and creates an outgoing stream of video pictures(411) that are uncompressed and that can be rendered on a display (412)(e.g., a display screen) or other rendering devices (not depicted). Thevideo decoder 410 may be configured to perform some or all of thevarious functions described in this disclosure. In some streamingsystems, the encoded video data (404), (407), and (409) (e.g., videobitstreams) can be encoded according to certain video coding/compressionstandards. Examples of those standards include ITU-T RecommendationH.265. In an example, a video coding standard under development isinformally known as Versatile Video Coding (VVC). The disclosed subjectmatter may be used in the context of VVC, and other video codingstandards.

It is noted that the electronic devices (420) and (430) can includeother components (not shown). For example, the electronic device (420)can include a video decoder (not shown) and the electronic device (430)can include a video encoder (not shown) as well.

FIG. 5 shows a block diagram of a video decoder (510) according to anyembodiment of the present disclosure below. The video decoder (510) canbe included in an electronic device (530). The electronic device (530)can include a receiver (531) (e.g., receiving circuitry). The videodecoder (510) can be used in place of the video decoder (410) in theexample of FIG. 4 .

The receiver (531) may receive one or more coded video sequences to bedecoded by the video decoder (510). In the same or another embodiment,one coded video sequence may be decoded at a time, where the decoding ofeach coded video sequence is independent from other coded videosequences. Each video sequence may be associated with multiple videoframes or images. The coded video sequence may be received from achannel (501), which may be a hardware/software link to a storage devicewhich stores the encoded video data or a streaming source whichtransmits the encoded video data. The receiver (531) may receive theencoded video data with other data such as coded audio data and/orancillary data streams, that may be forwarded to their respectiveprocessing circuitry (not depicted). The receiver (531) may separate thecoded video sequence from the other data. To combat network jitter, abuffer memory (515) may be disposed in between the receiver (531) and anentropy decoder/parser (520) (“parser (520)” henceforth). In certainapplications, the buffer memory (515) may be implemented as part of thevideo decoder (510). In other applications, it can be outside of andseparate from the video decoder (510) (not depicted). In still otherapplications, there can be a buffer memory (not depicted) outside of thevideo decoder (510) for the purpose of, for example, combating networkjitter, and there may be another additional buffer memory (515) insidethe video decoder (510), for example to handle playback timing. When thereceiver (531) is receiving data from a store/forward device ofsufficient bandwidth and controllability, or from an isosynchronousnetwork, the buffer memory (515) may not be needed, or can be small. Foruse on best-effort packet networks such as the Internet, the buffermemory (515) of sufficient size may be required, and its size can becomparatively large. Such buffer memory may be implemented with anadaptive size, and may at least partially be implemented in an operatingsystem or similar elements (not depicted) outside of the video decoder(510).

The video decoder (510) may include the parser (520) to reconstructsymbols (521) from the coded video sequence. Categories of those symbolsinclude information used to manage operation of the video decoder (510),and potentially information to control a rendering device such asdisplay (512) (e.g., a display screen) that may or may not an integralpart of the electronic device (530) but can be coupled to the electronicdevice (530), as is shown in FIG. 5 . The control information for therendering device(s) may be in the form of Supplemental EnhancementInformation (SEI messages) or Video Usability Information (VUI)parameter set fragments (not depicted). The parser (520) mayparse/entropy-decode the coded video sequence that is received by theparser (520). The entropy coding of the coded video sequence can be inaccordance with a video coding technology or standard, and can followvarious principles, including variable length coding, Huffman coding,arithmetic coding with or without context sensitivity, and so forth. Theparser (520) may extract from the coded video sequence, a set ofsubgroup parameters for at least one of the subgroups of pixels in thevideo decoder, based upon at least one parameter corresponding to thesubgroups. The subgroups can include Groups of Pictures (GOPs),pictures, tiles, slices, macroblocks, Coding Units (CUs), blocks,Transform Units (TUs), Prediction Units (PUs) and so forth. The parser(520) may also extract from the coded video sequence information such astransform coefficients (e.g., Fourier transform coefficients), quantizerparameter values, motion vectors, and so forth.

The parser (520) may perform an entropy decoding/parsing operation onthe video sequence received from the buffer memory (515), so as tocreate symbols (521).

Reconstruction of the symbols (521) can involve multiple differentprocessing or functional units depending on the type of the coded videopicture or parts thereof (such as: inter and intra picture, inter andintra block), and other factors. The units that are involved and howthey are involved may be controlled by the subgroup control informationthat was parsed from the coded video sequence by the parser (520). Theflow of such subgroup control information between the parser (520) andthe multiple processing or functional units below is not depicted forsimplicity.

Beyond the functional blocks already mentioned, the video decoder (510)can be conceptually subdivided into a number of functional units asdescribed below. In a practical implementation operating undercommercial constraints, many of these functional units interact closelywith each other and can, at least partly, be integrated with oneanother. However, for the purpose of describing the various functions ofthe disclosed subject matter with clarity, the conceptual subdivisioninto the functional units is adopted in the disclosure below.

A first unit may include the scaler/inverse transform unit (551). Thescaler/inverse transform unit (551) may receive a quantized transformcoefficient as well as control information, including informationindicating which type of inverse transform to use, block size,quantization factor/parameters, quantization scaling matrices, and thelie as symbol(s) (521) from the parser (520). The scaler/inversetransform unit (551) can output blocks comprising sample values that canbe input into aggregator (555).

In some cases, the output samples of the scaler/inverse transform (551)can pertain to an intra coded block, i.e., a block that does not usepredictive information from previously reconstructed pictures, but canuse predictive information from previously reconstructed parts of thecurrent picture. Such predictive information can be provided by an intrapicture prediction unit (552). In some cases, the intra pictureprediction unit (552) may generate a block of the same size and shape ofthe block under reconstruction using surrounding block information thatis already reconstructed and stored in the current picture buffer (558).The current picture buffer (558) buffers, for example, partlyreconstructed current picture and/or fully reconstructed currentpicture. The aggregator (555), in some implementations, may add, on aper sample basis, the prediction information the intra prediction unit(552) has generated to the output sample information as provided by thescaler/inverse transform unit (551).

In other cases, the output samples of the scaler/inverse transform unit(551) can pertain to an inter coded, and potentially motion compensatedblock. In such a case, a motion compensation prediction unit (553) canaccess reference picture memory (557) to fetch samples used forinter-picture prediction. After motion compensating the fetched samplesin accordance with the symbols (521) pertaining to the block, thesesamples can be added by the aggregator (555) to the output of thescaler/inverse transform unit (551) (output of unit 551 may be referredto as the residual samples or residual signal) so as to generate outputsample information. The addresses within the reference picture memory(557) from where the motion compensation prediction unit (553) fetchesprediction samples can be controlled by motion vectors, available to themotion compensation prediction unit (553) in the form of symbols (521)that can have, for example X, Y components (shift), and referencepicture components (time). Motion compensation may also includeinterpolation of sample values as fetched from the reference picturememory (557) when sub-sample exact motion vectors are in use, and mayalso be associated with motion vector prediction mechanisms, and soforth.

The output samples of the aggregator (555) can be subject to variousloop filtering techniques in the loop filter unit (556). Videocompression technologies can include in-loop filter technologies thatare controlled by parameters included in the coded video sequence (alsoreferred to as coded video bitstream) and made available to the loopfilter unit (556) as symbols (521) from the parser (520), but can alsobe responsive to meta-information obtained during the decoding ofprevious (in decoding order) parts of the coded picture or coded videosequence, as well as responsive to previously reconstructed andloop-filtered sample values. Several type of loop filters may beincluded as part of the loop filter unit 556 in various orders, as willbe described in further detail below.

The output of the loop filter unit (556) can be a sample stream that canbe output to the rendering device (512) as well as stored in thereference picture memory (557) for use in future inter-pictureprediction.

Certain coded pictures, once fully reconstructed, can be used asreference pictures for future inter-picture prediction. For example,once a coded picture corresponding to a current picture is fullyreconstructed and the coded picture has been identified as a referencepicture (by, for example, the parser (520)), the current picture buffer(558) can become a part of the reference picture memory (557), and afresh current picture buffer can be reallocated before commencing thereconstruction of the following coded picture.

The video decoder (510) may perform decoding operations according to apredetermined video compression technology adopted in a standard, suchas ITU-T Rec. H.265. The coded video sequence may conform to a syntaxspecified by the video compression technology or standard being used, inthe sense that the coded video sequence adheres to both the syntax ofthe video compression technology or standard and the profiles asdocumented in the video compression technology or standard.Specifically, a profile can select certain tools from all the toolsavailable in the video compression technology or standard as the onlytools available for use under that profile. To be standard-compliant,the complexity of the coded video sequence may be within bounds asdefined by the level of the video compression technology or standard. Insome cases, levels restrict the maximum picture size, maximum framerate, maximum reconstruction sample rate (measured in, for examplemegasamples per second), maximum reference picture size, and so on.Limits set by levels can, in some cases, be further restricted throughHypothetical Reference Decoder (HRD) specifications and metadata for HRDbuffer management signaled in the coded video sequence.

In some example embodiments, the receiver (531) may receive additional(redundant) data with the encoded video. The additional data may beincluded as part of the coded video sequence(s). The additional data maybe used by the video decoder (510) to properly decode the data and/or tomore accurately reconstruct the original video data. Additional data canbe in the form of, for example, temporal, spatial, or signal noise ratio(SNR) enhancement layers, redundant slices, redundant pictures, forwarderror correction codes, and so on.

FIG. 6 shows a block diagram of a video encoder (603) according to anexample embodiment of the present disclosure. The video encoder (603)may be included in an electronic device (620). The electronic device(620) may further include a transmitter (640) (e.g., transmittingcircuitry). The video encoder (603) can be used in place of the videoencoder (403) in the example of FIG. 4 .

The video encoder (603) may receive video samples from a video source(601) (that is not part of the electronic device (620) in the example ofFIG. 6 ) that may capture video image(s) to be coded by the videoencoder (603). In another example, the video source (601) may beimplemented as a portion of the electronic device (620).

The video source (601) may provide the source video sequence to be codedby the video encoder (603) in the form of a digital video sample streamthat can be of any suitable bit depth (for example: 8 bit, 10 bit, 12bit, . . . ), any colorspace (for example, BT.601 YCrCb, RGB, XYZ . . .), and any suitable sampling structure (for example YCrCb 4:2:0, YCrCb4:4:4). In a media serving system, the video source (601) may be astorage device capable of storing previously prepared video. In avideoconferencing system, the video source (601) may be a camera thatcaptures local image information as a video sequence. Video data may beprovided as a plurality of individual pictures or images that impartmotion when viewed in sequence. The pictures themselves may be organizedas a spatial array of pixels, wherein each pixel can comprise one ormore samples depending on the sampling structure, color space, and thelike being in use. A person having ordinary skill in the art can readilyunderstand the relationship between pixels and samples. The descriptionbelow focuses on samples.

According to some example embodiments, the video encoder (603) may codeand compress the pictures of the source video sequence into a codedvideo sequence (643) in real time or under any other time constraints asrequired by the application. Enforcing appropriate coding speedconstitutes one function of a controller (650). In some embodiments, thecontroller (650) may be functionally coupled to and control otherfunctional units as described below. The coupling is not depicted forsimplicity. Parameters set by the controller (650) can include ratecontrol related parameters (picture skip, quantizer, lambda value ofrate-distortion optimization techniques, . . . ), picture size, group ofpictures (GOP) layout, maximum motion vector search range, and the like.The controller (650) can be configured to have other suitable functionsthat pertain to the video encoder (603) optimized for a certain systemdesign.

In some example embodiments, the video encoder (603) may be configuredto operate in a coding loop. As an oversimplified description, in anexample, the coding loop can include a source coder (630) (e.g.,responsible for creating symbols, such as a symbol stream, based on aninput picture to be coded, and a reference picture(s)), and a (local)decoder (633) embedded in the video encoder (603). The decoder (633)reconstructs the symbols to create the sample data in a similar manneras a (remote) decoder would create even though the embedded decoder 633process coded video steam by the source coder 630 without entropy coding(as any compression between symbols and coded video bitstream in entropycoding may be lossless in the video compression technologies consideredin the disclosed subject matter). The reconstructed sample stream(sample data) is input to the reference picture memory (634). As thedecoding of a symbol stream leads to bit-exact results independent ofdecoder location (local or remote), the content in the reference picturememory (634) is also bit exact between the local encoder and remoteencoder. In other words, the prediction part of an encoder “sees” asreference picture samples exactly the same sample values as a decoderwould “see” when using prediction during decoding. This fundamentalprinciple of reference picture synchronicity (and resulting drift, ifsynchronicity cannot be maintained, for example because of channelerrors) is used to improve coding quality.

The operation of the “local” decoder (633) can be the same as of a“remote” decoder, such as the video decoder (510), which has alreadybeen described in detail above in conjunction with FIG. 5 . Brieflyreferring also to FIG. 5 , however, as symbols are available andencoding/decoding of symbols to a coded video sequence by an entropycoder (645) and the parser (520) can be lossless, the entropy decodingparts of the video decoder (510), including the buffer memory (515), andparser (520) may not be fully implemented in the local decoder (633) inthe encoder.

An observation that can be made at this point is that any decodertechnology except the parsing/entropy decoding that may only be presentin a decoder also may necessarily need to be present, in substantiallyidentical functional form, in a corresponding encoder. For this reason,the disclosed subject matter may at times focus on decoder operation,which allies to the decoding portion of the encoder. The description ofencoder technologies can thus be abbreviated as they are the inverse ofthe comprehensively described decoder technologies. Only in certainareas or aspects a more detail description of the encoder is providedbelow.

During operation in some example implementations, the source coder (630)may perform motion compensated predictive coding, which codes an inputpicture predictively with reference to one or more previously codedpicture from the video sequence that were designated as “referencepictures.” In this manner, the coding engine (632) codes differences (orresidue) in the color channels between pixel blocks of an input pictureand pixel blocks of reference picture(s) that may be selected asprediction reference(s) to the input picture. The term “residue” and itsadjective form “residual” may be used interchangeably.

The local video decoder (633) may decode coded video data of picturesthat may be designated as reference pictures, based on symbols createdby the source coder (630). Operations of the coding engine (632) mayadvantageously be lossy processes. When the coded video data may bedecoded at a video decoder (not shown in FIG. 6 ), the reconstructedvideo sequence typically may be a replica of the source video sequencewith some errors. The local video decoder (633) replicates decodingprocesses that may be performed by the video decoder on referencepictures and may cause reconstructed reference pictures to be stored inthe reference picture cache (634). In this manner, the video encoder(603) may store copies of reconstructed reference pictures locally thathave common content as the reconstructed reference pictures that will beobtained by a far-end (remote) video decoder (absent transmissionerrors).

The predictor (635) may perform prediction searches for the codingengine (632). That is, for a new picture to be coded, the predictor(635) may search the reference picture memory (634) for sample data (ascandidate reference pixel blocks) or certain metadata such as referencepicture motion vectors, block shapes, and so on, that may serve as anappropriate prediction reference for the new pictures. The predictor(635) may operate on a sample block-by-pixel block basis to findappropriate prediction references. In some cases, as determined bysearch results obtained by the predictor (635), an input picture mayhave prediction references drawn from multiple reference pictures storedin the reference picture memory (634).

The controller (650) may manage coding operations of the source coder(630), including, for example, setting of parameters and subgroupparameters used for encoding the video data.

Output of all aforementioned functional units may be subjected toentropy coding in the entropy coder (645). The entropy coder (645)translates the symbols as generated by the various functional units intoa coded video sequence, by lossless compression of the symbols accordingto technologies such as Huffman coding, variable length coding,arithmetic coding, and so forth.

The transmitter (640) may buffer the coded video sequence(s) as createdby the entropy coder (645) to prepare for transmission via acommunication channel (660), which may be a hardware/software link to astorage device which would store the encoded video data. The transmitter(640) may merge coded video data from the video coder (603) with otherdata to be transmitted, for example, coded audio data and/or ancillarydata streams (sources not shown).

The controller (650) may manage operation of the video encoder (603).During coding, the controller (650) may assign to each coded picture acertain coded picture type, which may affect the coding techniques thatmay be applied to the respective picture. For example, pictures oftenmay be assigned as one of the following picture types:

An Intra Picture (I picture) may be one that may be coded and decodedwithout using any other picture in the sequence as a source ofprediction. Some video codecs allow for different types of intrapictures, including, for example Independent Decoder Refresh (“IDR”)Pictures. A person having ordinary skill in the art is aware of thosevariants of I pictures and their respective applications and features.

A predictive picture (P picture) may be one that may be coded anddecoded using intra prediction or inter prediction using at most onemotion vector and reference index to predict the sample values of eachblock.

A bi-directionally predictive picture (B Picture) may be one that may becoded and decoded using intra prediction or inter prediction using atmost two motion vectors and reference indices to predict the samplevalues of each block. Similarly, multiple-predictive pictures can usemore than two reference pictures and associated metadata for thereconstruction of a single block.

Source pictures commonly may be subdivided spatially into a plurality ofsample coding blocks (for example, blocks of 4×4, 8×8, 4×8, or 16×16samples each) and coded on a block-by-block basis. Blocks may be codedpredictively with reference to other (already coded) blocks asdetermined by the coding assignment applied to the blocks' respectivepictures. For example, blocks of I pictures may be codednon-predictively or they may be coded predictively with reference toalready coded blocks of the same picture (spatial prediction or intraprediction). Pixel blocks of P pictures may be coded predictively, viaspatial prediction or via temporal prediction with reference to onepreviously coded reference picture. Blocks of B pictures may be codedpredictively, via spatial prediction or via temporal prediction withreference to one or two previously coded reference pictures. The sourcepictures or the intermediate processed pictures may be subdivided intoother types of blocks for other purposes. The division of coding blocksand the other types of blocks may or may not follow the same manner, asdescribed in further detail below.

The video encoder (603) may perform coding operations according to apredetermined video coding technology or standard, such as ITU-T Rec.H.265. In its operation, the video encoder (603) may perform variouscompression operations, including predictive coding operations thatexploit temporal and spatial redundancies in the input video sequence.The coded video data may accordingly conform to a syntax specified bythe video coding technology or standard being used.

In some example embodiments, the transmitter (640) may transmitadditional data with the encoded video. The source coder (630) mayinclude such data as part of the coded video sequence. The additionaldata may comprise temporal/spatial/SNR enhancement layers, other formsof redundant data such as redundant pictures and slices, SEI messages,VUI parameter set fragments, and so on.

A video may be captured as a plurality of source pictures (videopictures) in a temporal sequence. Intra-picture prediction (oftenabbreviated to intra prediction) utilizes spatial correlation in a givenpicture, and inter-picture prediction utilizes temporal or othercorrelation between the pictures. For example, a specific picture underencoding/decoding, which is referred to as a current picture, may bepartitioned into blocks. A block in the current picture, when similar toa reference block in a previously coded and still buffered referencepicture in the video, may be coded by a vector that is referred to as amotion vector. The motion vector points to the reference block in thereference picture, and can have a third dimension identifying thereference picture, in case multiple reference pictures are in use.

In some example embodiments, a bi-prediction technique can be used forinter-picture prediction. According to such bi-prediction technique, tworeference pictures, such as a first reference picture and a secondreference picture that both proceed the current picture in the video indecoding order (but may be in the past or future, respectively, indisplay order) are used. A block in the current picture can be coded bya first motion vector that points to a first reference block in thefirst reference picture, and a second motion vector that points to asecond reference block in the second reference picture. The block can bejointly predicted by a combination of the first reference block and thesecond reference block.

Further, a merge mode technique may be used in the inter-pictureprediction to improve coding efficiency.

According to some example embodiments of the disclosure, predictions,such as inter-picture predictions and intra-picture predictions areperformed in the unit of blocks. For example, a picture in a sequence ofvideo pictures is partitioned into coding tree units (CTU) forcompression, the CTUs in a picture may have the same size, such as 64×64pixels, 32×32 pixels, or 16×16 pixels. In general, a CTU may includethree parallel coding tree blocks (CTBs): one luma CTB and two chromaCTBs. Each CTU can be recursively quadtree split into one or multiplecoding units (CUs). For example, a CTU of 64×64 pixels can be split intoone CU of 64×64 pixels, or 4 CUs of 32×32 pixels. Each of the one ormore of the 32×32 block may be further split into 4 CUs of 16×16 pixels.In some example embodiments, each CU may be analyzed during encoding todetermine a prediction type for the CU among various prediction typessuch as an inter prediction type or an intra prediction type. The CU maybe split into one or more prediction units (PUs) depending on thetemporal and/or spatial predictability. Generally, each PU includes aluma prediction block (PB), and two chroma PBs. In an embodiment, aprediction operation in coding (encoding/decoding) is performed in theunit of a prediction block. The split of a CU into PU (or PBs ofdifferent color channels) may be performed in various spatial pattern. Aluma or chroma PB, for example, may include a matrix of values (e.g.,luma values) for samples, such as 8×8 pixels, 16×16 pixels, 8×16 pixels,16×8 samples, and the like.

FIG. 7 shows a diagram of a video encoder (703) according to anotherexample embodiment of the disclosure. The video encoder (703) isconfigured to receive a processing block (e.g., a prediction block) ofsample values within a current video picture in a sequence of videopictures, and encode the processing block into a coded picture that ispart of a coded video sequence. The example video encoder (703) may beused in place of the video encoder (403) in the FIG. 4 example.

For example, the video encoder (703) receives a matrix of sample valuesfor a processing block, such as a prediction block of 8×8 samples, andthe like. The video encoder (703) then determines whether the processingblock is best coded using intra mode, inter mode, or bi-prediction modeusing, for example, rate-distortion optimization (RDO). When theprocessing block is determined to be coded in intra mode, the videoencoder (703) may use an intra prediction technique to encode theprocessing block into the coded picture; and when the processing blockis determined to be coded in inter mode or bi-prediction mode, the videoencoder (703) may use an inter prediction or bi-prediction technique,respectively, to encode the processing block into the coded picture. Insome example embodiments, a merge mode may be used as a submode of theinter picture prediction where the motion vector is derived from one ormore motion vector predictors without the benefit of a coded motionvector component outside the predictors. In some other exampleembodiments, a motion vector component applicable to the subject blockmay be present. Accordingly, the video encoder (703) may includecomponents not explicitly shown in FIG. 7 , such as a mode decisionmodule, to determine the perdition mode of the processing blocks.

In the example of FIG. 7 , the video encoder (703) includes an interencoder (730), an intra encoder (722), a residue calculator (723), aswitch (726), a residue encoder (724), a general controller (721), andan entropy encoder (725) coupled together as shown in the examplearrangement in FIG. 7 .

The inter encoder (730) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to one ormore reference blocks in reference pictures (e.g., blocks in previouspictures and later pictures in display order), generate inter predictioninformation (e.g., description of redundant information according tointer encoding technique, motion vectors, merge mode information), andcalculate inter prediction results (e.g., predicted block) based on theinter prediction information using any suitable technique. In someexamples, the reference pictures are decoded reference pictures that aredecoded based on the encoded video information using the decoding unit633 embedded in the example encoder 620 of FIG. 6 (shown as residualdecoder 728 of FIG. 7 , as described in further detail below).

The intra encoder (722) is configured to receive the samples of thecurrent block (e.g., a processing block), compare the block to blocksalready coded in the same picture, and generate quantized coefficientsafter transform, and in some cases also to generate intra predictioninformation (e.g., an intra prediction direction information accordingto one or more intra encoding techniques). The intra encoder (722) maycalculates intra prediction results (e.g., predicted block) based on theintra prediction information and reference blocks in the same picture.

The general controller (721) may be configured to determine generalcontrol data and control other components of the video encoder (703)based on the general control data. In an example, the general controller(721) determines the prediction mode of the block, and provides acontrol signal to the switch (726) based on the prediction mode. Forexample, when the prediction mode is the intra mode, the generalcontroller (721) controls the switch (726) to select the intra moderesult for use by the residue calculator (723), and controls the entropyencoder (725) to select the intra prediction information and include theintra prediction information in the bitstream; and when the predicationmode for the block is the inter mode, the general controller (721)controls the switch (726) to select the inter prediction result for useby the residue calculator (723), and controls the entropy encoder (725)to select the inter prediction information and include the interprediction information in the bitstream.

The residue calculator (723) may be configured to calculate a difference(residue data) between the received block and prediction results for theblock selected from the intra encoder (722) or the inter encoder (730).The residue encoder (724) may be configured to encode the residue datato generate transform coefficients. For example, the residue encoder(724) may be configured to convert the residue data from a spatialdomain to a frequency domain to generate the transform coefficients. Thetransform coefficients are then subject to quantization processing toobtain quantized transform coefficients. In various example embodiments,the video encoder (703) also includes a residual decoder (728). Theresidual decoder (728) is configured to perform inverse-transform, andgenerate the decoded residue data. The decoded residue data can besuitably used by the intra encoder (722) and the inter encoder (730).For example, the inter encoder (730) can generate decoded blocks basedon the decoded residue data and inter prediction information, and theintra encoder (722) can generate decoded blocks based on the decodedresidue data and the intra prediction information. The decoded blocksare suitably processed to generate decoded pictures and the decodedpictures can be buffered in a memory circuit (not shown) and used asreference pictures.

The entropy encoder (725) may be configured to format the bitstream toinclude the encoded block and perform entropy coding. The entropyencoder (725) is configured to include in the bitstream variousinformation. For example, the entropy encoder (725) may be configured toinclude the general control data, the selected prediction information(e.g., intra prediction information or inter prediction information),the residue information, and other suitable information in thebitstream. When coding a block in the merge submode of either inter modeor bi-prediction mode, there may be no residue information.

FIG. 8 shows a diagram of an example video decoder (810) according toanother embodiment of the disclosure. The video decoder (810) isconfigured to receive coded pictures that are part of a coded videosequence, and decode the coded pictures to generate reconstructedpictures. In an example, the video decoder (810) may be used in place ofthe video decoder (410) in the example of FIG. 4 .

In the example of FIG. 8 , the video decoder (810) includes an entropydecoder (871), an inter decoder (880), a residual decoder (873), areconstruction module (874), and an intra decoder (872) coupled togetheras shown in the example arrangement of FIG. 8 .

The entropy decoder (871) can be configured to reconstruct, from thecoded picture, certain symbols that represent the syntax elements ofwhich the coded picture is made up. Such symbols can include, forexample, the mode in which a block is coded (e.g., intra mode, intermode, bi-predicted mode, merge submode or another submode), predictioninformation (e.g., intra prediction information or inter predictioninformation) that can identify certain sample or metadata used forprediction by the intra decoder (872) or the inter decoder (880),residual information in the form of, for example, quantized transformcoefficients, and the like. In an example, when the prediction mode isthe inter or bi-predicted mode, the inter prediction information isprovided to the inter decoder (880); and when the prediction type is theintra prediction type, the intra prediction information is provided tothe intra decoder (872). The residual information can be subject toinverse quantization and is provided to the residual decoder (873).

The inter decoder (880) may be configured to receive the interprediction information, and generate inter prediction results based onthe inter prediction information.

The intra decoder (872) may be configured to receive the intraprediction information, and generate prediction results based on theintra prediction information.

The residual decoder (873) may be configured to perform inversequantization to extract de-quantized transform coefficients, and processthe de-quantized transform coefficients to convert the residual from thefrequency domain to the spatial domain. The residual decoder (873) mayalso utilize certain control information (to include the QuantizerParameter (QP)) which may be provided by the entropy decoder (871) (datapath not depicted as this may be low data volume control informationonly).

The reconstruction module (874) may be configured to combine, in thespatial domain, the residual as output by the residual decoder (873) andthe prediction results (as output by the inter or intra predictionmodules as the case may be) to form a reconstructed block forming partof the reconstructed picture as part of the reconstructed video. It isnoted that other suitable operations, such as a deblocking operation andthe like, may also be performed to improve the visual quality.

It is noted that the video encoders (403), (603), and (703), and thevideo decoders (410), (510), and (810) can be implemented using anysuitable technique. In some example embodiments, the video encoders(403), (603), and (703), and the video decoders (410), (510), and (810)can be implemented using one or more integrated circuits. In anotherembodiment, the video encoders (403), (603), and (603), and the videodecoders (410), (510), and (810) can be implemented using one or moreprocessors that execute software instructions.

Returning to the intra prediction process, in which samples in a block(e.g., a luma or chroma prediction block, or coding block if not furthersplit into prediction blocks) is predicted by samples of neighboring,next neighboring, or other line or lines, or the combination thereof, togenerate a prediction block. The residual between the actual block beingcoded and the prediction block may then be processed via transformfollowed by quantization. Various intra prediction modes may be madeavailable and parameters related to intra mode selection and otherparameters may be signaled in the bitstream. The various intraprediction modes, for example, may pertain to line position or positionsfor predicting samples, directions along which prediction samples areselected from predicting line or lines, and other special intraprediction modes.

For example, a set of intra prediction modes (interchangeably referredto as “intra modes”) may include a predefined number of directionalintra prediction modes. As described above in relation to the exampleimplementation of FIG. 1 , these intra prediction modes may correspondto a predefined number of directions along which out-of-block samplesare selected as prediction for samples being predicted in a particularblock. In another particular example implementation, eight (8) maindirectional modes corresponding to angles from 45 to 207 degrees to thehorizontal axis may be supported and predefined.

In some other implementations of intra prediction, to further exploitmore varieties of spatial redundancy in directional textures,directional intra modes may be further extended to an angle set withfiner granularity. For example, the 8-angle implementation above may beconfigured to provide eight nominal angles, referred to as V_PRED,H_PRED, D45_PRED, D135_PRED, D113_PRED, D157_PRED, D203_PRED, andD67_PRED, as illustrated in FIG. 9 , and for each nominal angle, apredefined number (e.g., 7) of finer angles may be added. With such anextension, a larger total number (e.g., 56 in this example) ofdirectional angles may be available for intra prediction, correspondingto the same number of predefined directional intra modes. A predictionangle may be represented by a nominal intra angle plus an angle delta.For the particular example above with 7 finer angular directions foreach nominal angle, the angle delta may be −3˜3 multiplies a step sizeof 3 degrees.

In some implementations, alternative or in addition to the directionintra modes above, a predefined number of non-directional intraprediction modes may also be predefined and made available. For example,5 non-direction intra modes referred to as smooth intra prediction modesmay be specified. These non-directional intra mode prediction modes maybe specifically referred to as DC, PAETH, SMOOTH, SMOOTH_V, and SMOOTH_Hintra modes. Prediction of samples of a particular block under theseexample non-directional modes are illustrated in FIG. 10 . As anexample, FIG. 10 shows a 4×4 block 1002 being predicted by samples froma top neighboring line and/or left neighboring line. A particular sample1010 in block 1002 may correspond to directly top sample 1004 of thesample 1010 in the top neighboring line of block 1002, a top-left sample1006 of the sample 1010 as the intersection of the top and leftneighboring lines, and a directly left sample 1008 of the sample 1010 inthe left neighboring line of block 1002. For the example DC intraprediction mode, an average of the left and above neighboring samples1008 and 1004 may be used as the predictor of the sample 1010. For theexample PAETH intra prediction mode, the top, left, and top-leftreference samples 1004, 1008, and 1006 may be fetched, and thenwhichever value among these three reference samples that is the closestto (top+left−topleft) may be set as the predictor for the sample 1010.For the example SMOOTH_V intra prediction mode, the sample 1010 may bepredicted by a quadratic interpolation in vertical direction of thetop-left neighboring sample 1006 and the left neighboring sample 1008.For the example SMOOTH_H intra prediction mode, the sample 1010 may bepredicted by a quadratic interpolation in horizontal direction of thetop-left neighboring sample 1006 and the top neighboring sample 1004.For the example SMOOTH intra prediction mode, the sample 1010 may bepredicted by an average of the quadratic interpolations in the verticaland the horizontal directions. The non-directional intra modeimplementations above are merely illustrated as a non-limiting example.Other neighboring lines, and other non-directional selection of samples,and manners of combining predicting samples for predicting a particularsample in a prediction block are also contemplated.

Selection of a particular intra prediction mode by the encoder from thedirectional or non-directional modes above at various coding levels(picture, slice, block, unit, etc.) may be signaled in the bitstream. Insome example implementations, the exemplary 8 nominal directional modestogether with 5 non-angular smooth modes (a total of 13 options) may besignaled first. Then if the signaled mode is one of the 8 nominalangular intra modes, an index is further signaled to indicate theselected angle delta to the corresponding signaled nominal angle. Insome other example implementations, all intra prediction modes may beindexed all together (e.g., 56 directional modes plus 5 non-directionalmodes to yield 61 intra prediction modes) for signaling.

In some example implementations, the example 56 or other number ofdirectional intra prediction modes may be implemented with a unifieddirectional predictor that projects each sample of a block to areference sub-sample location and interpolates the reference sample by a2-tap bilinear filter.

In some implementations, to capture decaying spatial correlation withreferences on the edges, additional filter modes referred to as FILTERINTRA modes may be designed. For these modes, predicted samples withinthe block in addition to out-of-block samples may be used as intraprediction reference samples for some patches within the block. Thesemodes, for example, may be predefined and made available to intraprediction for at least luma blocks (or only luma blocks). A predefinednumber (e.g., five) of filter intra modes may be pre-designed, eachrepresented by a set of n-tap filters (e.g., 7-tap filters) reflectingcorrelation between samples in, for example, a 4×2 patch and n neighborsadjacent to it. In other words, the weighting factors for an n-tapfilter may be position dependent. Taking an 8×8 block, 4×2 patch, and7-tap filtering as an example, as shown in FIG. 11 , the 8×8 block 1102may be split into eight 4×2 patches. These patches are indicated by B0,B1, B1, B3, B4, B5, B6, and B7 in FIG. 11 . For each patch, its 7neighbors, indicated by R0˜R7 in FIG. 11 , may be used to predict thesamples in a current patch. For patch B0, all the neighbors may havebeen already reconstructed. But for other patches, some of the neighborsare in the current block and thus may not have been reconstructed, thenthe predicted values of immediate neighbors are used as the reference.For example, all the neighbors of patch B7 as indicated in FIG. 11 arenot reconstructed, so the prediction samples of neighbors are usedinstead.

In some implementation of intra prediction, one color component may bepredicted using one or more other color components. A color componentmay be any one of components in YCrCb, RGB, XYZ color space and thelike. For example, a prediction of chroma component (e.g., chroma block)from luma component (e.g., luma reference samples), referred to asChroma from Luma, or CfL), may be implemented. In some exampleimplementations, cross-color prediction many only be allowed from lumato chroma. For example, a chroma sample in a chroma block may be modeledas a linear function of coincident reconstructed luma samples. The CfLprediction may be implemented as follows:CƒL(α)=α×L ^(AC) +DC  (1)where L^(AC) denotes an AC contribution of luma component, α denotes aparameter of the linear model, and DC denotes a DC contribution of thechroma component. The AC components, for example is obtained for eachsamples of the block whereas the DC component is obtained for the entireblock. To be specific, the reconstructed luma samples may be subsampledinto the chroma resolution, and then the average luma value (DC of luma)may be subtracted from each luma value to form the AC contribution inluma. The AC contribution of Luma is then used in the linear mode of Eq.(1) to predict the AC values of the chroma component. To approximate orpredict chroma AC component from the luma AC contribution, instead ofrequiring the decoder to calculate the scaling parameters, an exampleCfL implementation may determine the parameter a based on the originalchroma samples and signal them in the bitstream. This reduces decodercomplexity and yields more precise predictions. As for the DCcontribution of the chroma component, it may be computed using intra DCmode within the chroma component in some example implementations.

Transform of a residual of either an intra prediction block or an interprediction block may then be implemented followed by quantization of thetransform coefficient. For the purpose of performing transform, bothintra and inter coded blocks may be further partitioned into multipletransform blocks (sometimes interchangeably used as “transform units”,even though the term “unit” is normally used to represent a congregationof the three-color channels, e.g., a “coding unit” would include lumacoding block, and chroma coding blocks) prior to the transform. In someimplementations, the maximum partitioning depth of the coded blocks (orprediction blocks) may be specified (the term “coded blocks” may be usedinterchangeably with “coding blocks”). For example, such partitioningmay not go beyond 2 levels. The division of prediction block intotransform blocks may be handled differently between intra predictionblocks and inter prediction blocks. In some implementations, however,such division may be similar between intra prediction blocks and interprediction blocks.

In some example implementations, and for intra coded blocks, thetransform partition may be done in a way that all the transform blockshave the same size, and the transform blocks are coded in a raster scanorder. An example of such transform block partitioning of an intra codedblock is shown in FIG. 12 . Specifically, FIG. 12 illustrates the codedblock 1202 is partitioned via an intermediate level quadtree splitting1204 into 16 transform blocks of the same block size, as shown by 1206.The example raster scan order for coding is illustrated by the orderedarrows in FIG. 12 .

In some example implementations, and for inter coded blocks, thetransform unit partitioning may be done in a recursive manner with thepartitioning depth up to a predefined number of levels (e.g., 2 levels).Split may stop or continue recursively for any sub partition and at anylevel, as shown in FIG. 13 . In particular, FIG. 13 shows an examplewhere the block 1302 is split into four quadtree sub blocks 1304 and oneof the subblocks is further split into four second level transformblocks whereas division of the other subblocks stops after the firstlevel, yielding a total of 7 transform blocks of two different sizes.The example raster scan order for coding is further illustrated by theordered arrows in FIG. 13 . While FIG. 13 shows an exampleimplementation of quadtree split of up-to two levels of square transformblocks, in some generation implementations, the transform partitioningmay support 1:1 (square), 1:2/2:1, and 1:4/4:1 transform block shapesand sizes ranging from 4×4 to 64×64. In some example implementations, ifthe coding block is smaller than or equal to 64×64, the transform blockpartitioning may only be applied to luma component (in other words, thechroma transform block would be the same as the coding block under thatcondition). Otherwise, if the coding block width or height is greaterthan 64, both the luma and chroma coding blocks may be implicitly splitinto multiples of min (W, 64)×min (H, 64) and min (W, 32)×min (H, 32)transform blocks, respectively.

Each of the transform blocks above may then be subject to a primarytransform. The primary transform essentially moves the residual in atransform block from spatial domain to frequency domain. In someimplementation of the actual primary transform, in order to support theexample extended coding block partitions above, multiple transform sizes(ranging from 4-point to 64-point for each dimension of the twodimensions) and transform shapes (square; rectangular with width/heightratio's 2:1/1:2, and 4:1/1:4) may be allowed.

Turning to the actual primary transform, in some exampleimplementations, a 2-D transform process may involve a use of hybridtransform kernels (which, for example, may be composed of different 1-Dtransforms for each dimension of the coded residual transform block).Example 1-D transform kernels may include but are not limited to: a)4-point, 8-point, 16-point, 32-point, 64-point DCT-2; b) 4-point,8-point, 16-point asymmetric DST's (DST-4, DST-7) and their flippedversions; c) 4-point, 8-point, 16-point, 32-point identity transforms.Selection of transform kernels to be used for each dimension may bebased on a rate-distortion (RD) criterion. For example, the basisfunctions for the DCT-2 and asymmetric DST's that may be implemented arelisted in Table 1.

TABLE 1 Example primary transform basis functions (DCT-2, DST-4 andDST-7 for N-point input). Transform Type Basis function T_(i)(j), i, j =0, 1, . . . , N − 1 DCT-2${T_{i}(j)} = {\omega_{0} \cdot \sqrt{\frac{2}{N}} \cdot {\cos( \frac{\pi \cdot i \cdot ( {{2j} + 1} )}{2N} )}}$${{where}\omega_{0}} = \{ \begin{matrix}\sqrt{\frac{2}{N}} & {i = 0} \\1 & {i \neq 0}\end{matrix} $ DST-4${T_{i}(j)} = {\sqrt{\frac{2}{N}} \cdot {\sin( \frac{\pi \cdot ( {{2i} + 1} ) \cdot ( {{2j} + 1} )}{4N} )}}$DST-7${T_{i}(j)} = {\sqrt{\frac{4}{{2N} + 1}} \cdot {\sin( \frac{\pi \cdot ( {{2i} + 1} ) \cdot ( {j + 1} )}{{2N} + 1} )}}$

In some example implementations, the availability of hybrid transformkernels for a particular primary transform implementation may be basedon the transform block size and prediction mode. An example dependencyis listed in Table 2. For a chroma component, the transform typeselection may be performed in an implicit way. For example, for intraprediction residuals, the transform type may be selected according tothe intra prediction mode, as specified in Table 3. For inter predictionresiduals, the transform type for chroma blocks may be selectedaccording to the transform type selection of the co-located luma blocks.Therefore, for chroma component, there is no transform type signaling inthe bitstream.

TABLE 2 AV1 hybrid transform kernels and their availability based onprediction modes and block sizes. Here → and ↓ denote the horizontal andvertical dimensions; ✓ and x denotes the availability of a kernel forthat block size & prediction mode. Prediction mode Transform TypesDescription Intra Inter DCT_DCT DCT ↓ and → ✓ (all ✓ (all block blocksizes) sizes) ADST_DCT ADST ↓; DCT → ✓ (block ✓ (block DCT_ADST DCT ↓;ADST → size ≤ size ≤ ADST_ADST ADST ↓ and → 16 × 16) 16 × 16)FLIPADST_DCT FLIPADST ↓; x ✓ (block DCT → size ≤ DCT_FLIPADST DCT ↓; 16× 16) FLIPADST → FLIPADST_FLIPADST FLIPADST ↓ and → ADST_FLIPADST ADST↓; FLIPADST → FLIPADST_ADST FLIPADST ↓; ADST → IDTX IDTX ↓ and → ✓(block ✓ (block size ≤ size ≤ 16 × 16) 32 × 32) V_DCT DCT ↓; IDTX → ✓(block ✓ (block H_DCT IDTX ↓; DCT → size < size ≤ 16 × 16) 16 × 16)V_ADST ADST ↓; IDTX → x ✓ (block H_ADST IDTX ↓; ADST → size < 16 × 16)V_FLIPADST FLIPADST ↓; x ✓ (block IDTX → size < H_FLIPADST IDTX ↓; 16 ×16) FLIPADST →

TABLE 3 Transform type selection for chroma component intra predictionresiduals. Intra prediction Vertical Transform Horizontal TransformDC_PRED DCT DCT V_PRED ADST DCT H_PRED DCT ADST D45_PRED DCT DCTD135_PRED ADST ADST D113_PRED ADST DCT D157_PRED DCT ADST D203_PRED DCTADST D67_PRED ADST DCT SMOOTH_PRED ADST ADST SMOOTH_V_PRED ADST DCTSMOOTH_H_PRED DCT ADST PAETH_PRED ADST ADST

In some implementation, secondary transform on the primary transformcoefficients may be performed. For example, LFNST (low-frequencynon-separable transform), which is known as reduced secondary transformmay be applied between forward primary transform and quantization (atencoder) and between de-quantization and inverse primary transform (atdecoder side), as shown in FIG. 14 , to further decorrelate the primarytransform coefficients. In essence, LFNST may take a portion of theprimary transform coefficient, e.g., the low frequency portion (hence“reduced” from the full set of primary transform coefficients of thetransform block) to proceed to secondary transform. In an example LFNST,4×4 non-separable transform or 8×8 non-separable transform may beapplied according to transform block size. For example, 4×4 LFNST may beapplied for small transform blocks (e.g., min (width, height)<8) whereas8×8 LFNST may be applied for larger transform blocks (e.g., min (width,height)>8). For example, if an 8×8 transform block is subject to 4×4LFNST, then only the low frequency 4×4 portion of the 8×8 primarytransform coefficients is further undergo secondary transform.

As specifically shown in FIG. 14 , a transform block may be 8×8 (or16×16). Thus, the forward primary transform 1402 of the transform blockyields a 8×8 (or 16×16) primary transform coefficient matrix 1404, whereeach square unit represent a 2×2 (or 4×4) portion. The input to theforward LFNST, for example, may not be the entire 8×8 (or 16×16) primarytransform coefficients. For example, a 4×4 (or 8×8) LFNST may be usedfor secondary transform. As such, only the 4×4 (or 8×8) low frequencyprimary transform coeffects of the primary transform coefficient matrix1404, as indicated in the shaded portion (upper left) 1406 may be usedas input to the LFNST. The remaining portions of the primary transformcoefficient matrix may not be subject to secondary transform. As such,after the secondary transform, the portion of the primary transformcoeffects subject to the LFNST becomes the secondary transformcoefficients whereas the remaining portions not subject to LFNST (e.g.,the unshaded portions of the matrix 1404) maintain the correspondingprimary transform coefficients. In some example implementations, theremaining portion not subject of secondary transform may be all set tozero coefficient.

An example for application of a non-separable transform used in LFNST,is described below. To apply an example 4×4 LFNST, the 4×4 input block X(representing, e.g., the 4×4 low-frequency portion of a primarytransform coefficient block such as the shaded portion 1406 of theprimary transform matrix 1404 of FIG. 14 ) may be denoted as:

$\begin{matrix}{X = \begin{bmatrix}X_{00} & X_{01} & X_{02} & X_{03} \\X_{10} & X_{11} & X_{12} & X_{13} \\X_{20} & X_{21} & X_{22} & X_{23} \\X_{30} & X_{31} & X_{32} & X_{33}\end{bmatrix}} & (2)\end{matrix}$

This 2-D input matrix may be first linearized or scanned to a vector

in an example order:

=[X₀₀ X₀₁ X₀₂ X₀₃ X₁₀ X₁₁ X₁₂ X₁₃ X₂₀ X₂₁ X₂₂ X₂₃ X₃₀ X₃₂ X₃₃]³  (3)

The non-separable transform for the 4×4 LFNST may then be calculated as

=T·

, where

indicates the output transform coefficient vector, and T is a 16×16transform matrix. The resulting 16×1 coefficient vector

is subsequently reverse scanned as 4×4 block using the scanning orderfor that block (e.g., horizontal, vertical or diagonal). Thecoefficients with smaller index may be placed with the smaller scanningindex in the 4×4 coefficient block. In such a manner, redundancy in aprimary transform coefficients X may be further exploit via the secondtransform T, thereby providing additional compression enhancement.

The example LFNST above is based on a direct matrix multiplicationapproach to apply non-separable transform so that it is implemented in asingle pass without multiple iterations. In some further exampleimplementations, the dimension of the non-separable transform matrix (T)for the example 4×4 LFNST may be further reduced to minimizecomputational complexity and memory space requirement for storing thetransform coefficients. Such implementations may be referred to asreduced non-separate transform (RST). In more detail, the main idea ofthe RST is to map an N (N is 4×4=16 in the example above, but may beequal to 64 for 8×8 blocks) dimensional vector to an R dimensionalvector in a different space, where N/R (R<N) represents the dimensionreduction factor. Hence, instead of N×N transform matrix, RST matrixbecomes an R x N matrix as follows:

$\begin{matrix}{T_{RxN} = \begin{bmatrix}t_{11} & t_{12} & t_{13} & & t_{1N} \\t_{21} & t_{22} & t_{23} & \cdots & t_{2N} \\ & \vdots & & \ddots & \vdots \\t_{R1} & t_{R2} & t_{R3} & \cdots & t_{RN}\end{bmatrix}} & (4)\end{matrix}$where the R rows of the transform matrix are reduced R basis of the Ndimensional space. The transformation thus converts an input vector or Ndimension to an output vector of reduced R dimension. As such, and asshown in FIG. 14 , the secondary transform coefficients 1408 transformedfrom the primary coefficients 1406 is reduced by a factor or N/R indimension. The three squares around 1408 in FIG. 14 may be zero-padded.

The inverse transform matrix for RTS may be the transpose of its forwardtransform. For an example 8×8 LFNST (contrasted with the 4×4 LFNSTabove, for a more diverse description here), an example reduction factorof 4 may be applied, and thus a 64×64 direct non-separable transformmatrix is accordingly reduced to 16×64 direct matrix. Further, in someimplementations, a portion rather than an entirety of the input primarycoefficients may be linearized into the input vector for the LFNST. Forexample, only a portion of the example 8×8 input primary transformcoefficients may be linearized into the X vector above. For a particularexample, out of the four 4×4 quadrants of the 8×8 primary transformcoefficient matrix, the bottom right (high frequency coefficients) maybe left out, and only the other three quadrants are linearized into a48×1 vector using a predefined scan order rather than a 64×1 vector. Insuch implementations, the non-separable transform matrix may be furtherreduced from 16×64 to 16×48.

Hence, an example reduced 48×16 inverse RST matrix may be used at thedecoder side to generate the top-left, top-right, and bottom-left 4×4quadrants of the 8×8 core (primary) transform coefficients.Specifically, when the further reduced 16×48 RST matrices are appliedinstead of the 16×64 RST with the same transform set configuration, thenon-separable secondary transformation would take as input thevectorized 48 matrix elements from three 4×4 quadrant blocks of the 8×8primary coefficient block excluding right-bottom 4×4 block. In suchimplementations the omitted right-bottom 4×4 primary transformcoefficient would be ignored in the secondary transformation. Thisfurther reduced transformation, would convert a vector of 48×1 into anoutput vector of 16×1, which is reverse scanned into a 4×4 matrix tofill 1408 of FIG. 14 . The three squares of the secondary transformcoefficients surrounding 1408 may be zero padded.

With the help of the such reduction of dimensions in the RST, memoryusage for storing all LFNST matrices is reduced. In the above example,the memory usage, for example, may be reduced from 10 KB to 8 KB withreasonably insignificant performance drop compared to the implementationwithout dimension reduction.

In some implementations, in order to reduce complexity, LFNST may befurther restricted to be applicable only if all coefficients outside theprimary transform coefficient portion to be subject to LFNST (e.g.,outside of the 1406 portion of 1404 in FIG. 14 ) are non-significant.Hence, all primary-only transform coefficients (e.g., the unshadedportion of the primary coefficient matrix 1404 of FIG. 4 ) may be nearzero when LFNST is applied. Such a restriction allows for a conditioningof the LFNST index signalling on the last-significant position, andhence avoids some extra coefficient scanning, which may be needed forchecking for significant coefficients at specific positions when thisrestriction is not applied. In some implementations, the worst-casehandling of LFNST (in terms of multiplications per pixel) may restrictthe non-separable transforms for 4×4 and 8×8 blocks to 8×16 and 8×48transforms, respectively. In those cases, the last-significant scanposition has to be less than 8, when LFNST is applied, for other sizesless than 16. For blocks with a shape of 4×N and N×4 and N>8, therestriction above implies that the LFNST is now applied only once to thetop-left 4×4 region only. As all primary-only coefficients are zero whenLFNST is applied, the number of operations needed for the primarytransforms is reduced in such cases. From an encoder perspective, thequantization of coefficients can be simplified when LFNST transforms aretested. A rate-distortion optimized quantization (RDO) has to be done atmaximum for the first 16 coefficients (in scan order), the remainingcoefficients may be enforced to be zero.

In some example implementations, the RST kernels available may bespecified as a number of transform sets with each transform setsincluding a number of non-separable transform matrices. For example,there may be a total of 4 transform sets and 2 non-separable transformmatrices (kernels) per transform set for used in LFNST. These kernelsmay be pre-trained offline and they are thus data driven. The offlinetrained transform kernels may be stored in memory or hard coded in anencoding or decoding device for use during encoding/decoding process. Aselection of the transform set during encoding or decoding process maybe determined by the intra prediction mode. A mapping from the intraprediction modes to the transform sets may be pre-defined. An example ofsuch predefined mapping is shown in Table 4. For example, as shown inTable 4, if one of three Cross-Component Linear Model (CCLM) modes(INTRA_LT_CCLM, INTRA_T_CCLM or INTRA_L_CCLM) is used for the currentblock (i.e., 81<=predModelntra<=83), transform set 0 may be selected forthe current chroma block. For each transform set, the selectednon-separable secondary transform candidate may be further specified bythe explicitly signalled LFNST index. For example, the index may besignalled in a bit-stream once per intra CU after transformcoefficients.

TABLE 4 Transform selection table IntraPredMode Tr. set indexIntraPredMode < 0 1 0 <= IntraPredMode <= 1 0  2 <= IntraPredMode <= 121 13 <= IntraPredMode <= 23 2 24 <= IntraPredMode <= 44 3 45 <=IntraPredMode <= 55 2 56 <= IntraPredMode <= 80 1 81 <= IntraPredMode <=83 0

Because LFNST is restricted to be applicable only if all coefficientsoutside the first coefficient sub-group or portion are non-significantin the example implementations above, LFNST index coding depends on theposition of the last significant coefficient. In addition, the LFNSTindex may be context coded but does not depend on intra prediction mode,and only the first bin may be context coded. Furthermore, LFNST may beapplied for intra CU in both intra and inter slices, and for both lumaand chroma. If a dual tree is enabled, LFNST indices for Luma and Chromamay be signaled separately. For inter slice (the dual tree is disabled),a single LFNST index may be signaled and used for both Luma and Chroma.

In some example implementations, when Intra Sub-Partitioning (ISP) modeis selected, LFNST may be disabled and RST index may not be signaled,because performance improvement is likely to be marginal even if RST isapplied to every feasible partition block. Furthermore, disabling RSTfor ISP-predicted residual could reduce encoding complexity. In somefurther implementations, LFNST may also be disabled and the RST indexmay not be signaled when Multiple linear regression Intra Prediction(MIP) mode is selected.

Considering that a large CU greater than 64×64 (or any other predefinedsizes representing the maximum transform block size) is implicitly split(e.g., TU tiling) due to the existing maximum transform size restriction(e.g., 64×64), an LFNST index search could increase data buffering byfour times for a certain number of decode pipeline stages. Therefore, insome implementations, the maximum size that LFNST is allowed may berestricted to, for example, 64×64. In some implementations, LFNST may beenabled with DCT2 as primary transform only.

In some other implementations, intra secondary transform (IST) isprovided for luma component by defining, e.g., 12 sets of secondarytransforms, with, e.g., 3 kernels in each set. An intra mode dependentindex may be used for transform set selection. The kernel selectionwithin a set may be based on a signaled syntax element. The IST may beenabled when either DCT2 or ADST is used as both horizontal and verticalprimary transform. In some implementations, according to the block size,a 4×4 non-separable transform or 8×8 non-separable transform can beselected. If min (tx_width, tx_height)<8 the 4×4 IST can be selected.For larger blocks 8×8 IST can be used. Here tx_width & tx_heightcorrespond to transform block width & height, respectively. The input toIST may be low frequency primary transform coefficients in a zig-zagscan order.

Utilization of data-driven or offline-trained transform kernels foreither primary or secondary transform, especially non-separabletransform kernels, may facilitate enhancement of coding performancecomparing to only using fixed transform such as DCT/DST. However,applying such data-driven transform kernels may increase complexity of avideo codec. For example, data-driven transform kernels may requiresignificant amount of memory for storing all possible kernels,especially for non-separable transforms. Specifically, for one of theexample implementations above, there may be 12 possible sets of kernels.Each set may include, e.g., 3 kernels for different LFNST (e.g., 4×4 and8×8). Further, LFNST kernels may be different for different primarytransform types (e.g., DCT or ADST primary type for which LFNST may beallowed). In other words, if memory is used for storing off-line trainedLFNST kernels, a significant amount of memory would be required. Thevarious implementations described below for using data-driven transformmay be designed to reduce the memory footprint of the stored kernels andcomplexity of the codec, as described in further detail below.

These various implementations or embodiments are merely examples. Theymay be used separately or may be combined in any order or manner.Further, each of the implementations may be embodied as methods, andencoder devices or decoder including processing circuitry (e.g., one ormore processors or one or more integrated circuits) to implement themethods. In one example, the processing circuitry may include one ormore processors that executing a program that is stored in anon-transitory computer-readable medium. In another example, theprocessing circuitry may be hard coded to implement the methods. In yetanother example, the processing circuitry may be a mixture of processercomponent for executing computer-readable instructions and hardcodedcircuitry.

In the example implementations below, the term “block” may beinterpreted as a prediction block or a coding block or the like. Theterm block here may also be used to refer to the transform block, whichas described above, may be a portion of a coding block. The term “size”of a block is used to refer to any of a width, a height, a block aspectratio, a block area size, or the minimum/maximum between width andheight of a block.

In the various example implementations below, one or more indices foridentifying one or more separable or non-separable transforms (ortransform kernels) among the set of separable or non-separable secondarytransforms used for decoding a current transform block may be signaledin a video bitstream. Each of such indices may be denoted as stIdx.These implementations may be applied to either primary transform,secondary transform, or additional transforms applied after secondarytransform. Further, the underlying principle can be applied to eitherseparable transform or non-separable transform.

In the example implementations below, the “term basis vector” is used torefer to a spatial frequency component of a transform kernel for imagetransform from spatial domain to frequency domain. The terms“high-frequency basis vector” and the like are used to refer to basisvectors that may be used to generate a transform coefficient that isscanned from low to high frequency components after N coefficients, itmay also refer to a basis vector that is located after N rows (orcolumns) of a non-separable transform kernel (and thus higher than afrequency corresponding to N). Example values of N include, but notlimited to any integer values between 1 and 128 (inclusive). Delineationof high and low frequency (the number N) may be determined via RDO.

In some general example implementations, when multiple transform kernelscan be applied and are provided as selectable options during encodingand decoding process, part of the basis vectors of those multipletransform kernels may be shared. For example, high frequency basisvectors between some or all of the multiple transform kernels may beshared whereas low frequency basis vectors may be individualized betweenthe multiple transform kernels. In such a matter, such offline trainedand data driven transform kernels may require less memory altogether. Inparticular, the shared basis vectors need not be duplicated and one copymay need to be kept in the memory between the sharing transform kernels.The manner in which the shared and individualized basis vectors arestored in the memory may be predefined.

Such implementations are illustrated in the FIG. 15 , showing an exampleof how the basis vectors are shared between two LFNST transform matricesor kernels that are used for forward secondary transform. The two blocks1502 and 1504 indicate two transform matrices, i.e., transform matrix A(left) and B (right), each row of the transform matrix represents onebasis vector, the bottom rows (shaded) refer to basis vectors that areshared between A and B. The bottom basis vector may be of higherfrequency. The higher frequency basis vectors may be shared in thememory between these example kernels. For inverse transform, the sharedbasis vectors of multiple transform matrices can be the right N columnsof the transform matrix as a result of transpose for reverse transform.

The example transform kernels of FIG. 15 are illustrated for secondarytransform kernels that are applied to linearized vectors of primarytransform coefficients. As such, the frequency axis of such transformkernel as shown in FIG. 15 is one dimensional (from top to bottom). Thiswould be the case for all 1-D kernels. For a transform kernel that are2-D (e.g., when data driven 2-D kernels are used for primary transform)then lower frequency components would be at the upper left portion ofthe 2-D transform kernel whereas higher frequency components would be atthe lower right portion of the 2-D transform kernel. In that case, thelower-right portions may be shared among different 2-D kernels.

In some example implementations, for a set of multiple transform kernelsthat are applied for a specific intra prediction mode, thehigh-frequency basis vectors may be constructed the same (shared), whilethe low-frequency basis vectors may be different (individualized). Inother words, a set of kernels corresponding to a particular intraprediction mode (e.g., the various direction, non-directional, and otherintra prediction modes described above) may have similar dimensionalityand thus may share, e.g., high frequency basis vectors withindividualized low frequency basis vectors. A predefined threshold maybe used for delineation of low and high frequencies. In someimplementations, the delineation of high and low frequencies may be datadriven and thus pretrained. As such, the frequency delineation thresholdmay be different for different intra prediction modes.

In some example implementations, when multiple secondary transformkernels are applied together with different primary transforms, part orall of the multiple secondary transform kernels can be shared betweenthe different primary transform types. In other words, different typesof primary transform may correspond to different kernels for secondarytransformation. These different secondary transform kernels may containindividualized low frequency basis vectors and are nevertheless beconstructed with shared high frequency basis vectors. That is, secondarytransform kernel selection, if applicable for multiple primary transformtypes, may be independent of the primary transform type (e.g.,independent of DCT or ADST primary transform types).

In some example implementations, when multiple secondary transformkernels are applied together with different primary transforms,high-frequency basis vectors in the multiple secondary transform kernelsmay be shared between the different primary transform types, while thelow-frequency basis vectors can be different or individualized. Apredefined threshold may be used for delineation of low and highfrequencies. Again, the delineation of high and low frequencies (or thenumber N) may be data driven and thus pretrained. As such, the frequencydelineation threshold may be different for different intra predictionmodes.

In some example implementations, for multiple secondary transformkernels that are applied together with a specific type of primarytransform, the high-frequency basis vectors may be the same, while thelow-frequency basis vectors may be different. In some furtherimplementations, both the high-frequency basis vectors and low frequencybase vectors of kernels corresponding to different primary transformtypes maybe independent.

In some example implementations, the number N of high frequency basisvectors of shared between various transform kernels may be integer powerof 2, e.g., 1, 2, 4, 8, 16, 32, 64, 128. Particularly for reducedsecondary transform matrix, the number of N high frequency rows may be apower-of-2 value, e.g., 1, 2, 4, 8, 16, 32, 64, 128.

In some example implementations, the value of N may depend on thetransform size. For examples, a ratio between N and the total number ofbasis vectors of the transform kernels may be specified.

In some examples, each of and any combination of the aboveimplementations may be applied to LFNST secondary transform. As such,the set of kernels sharing high frequency basis vectors but containingindividualized low frequency basis vectors may include secondary LFNSTtransform kernels.

In some examples, each of and any combination of the aboveimplementations may be applied to Intra Secondary Transform (IST).

In some examples, each of and any combination of the aboveimplementations may be applied to Line Graph Transform. (LGT).

The various kernels above may be predetermined. They may be pretrainedoffline. For kernels sharing high frequency basis vectors, they may bejointly trained. The threshold frequency delineating the shared basisvectors and the individualized basis vectors may be trained offline.

During encoding or decoding process, the various kernels above mayreside in a memory space for use by an encoder or decoder, only one copyof the shared basis vector need to be stored in the memory space.Pointers to the memory locations for the shared basis vector may be usedto access these shared basis vector when the various kernels are usedduring the encoding or decoding process.

FIG. 16 shows a flow chart 1600 of an example method following theprinciples underlying the implementations above. The example method flowstarts at 1601. In S1610, a plurality of transform kernels areidentified, wherein each of the plurality of transform kernels comprisesa set of basis vectors from low to high frequencies; N high-frequencybasis vectors of two or more of the plurality of transform kernels areshared, N being a positive integer; and low frequency basis vectors ofthe two or more of the plurality of the transform kernels other than theN high-frequency basis vectors are individualized. In S1620, a datablock is extracted from a video bitstream. In S1630, a transform kernelfrom the plurality of transform kernels is selected based on informationassociated with the data block. In S1640, the transform kernel isapplied to at least a portion of the data block to generate atransformed block. The example method flow 1600 ends at S1699.

Embodiments in the disclosure may be used separately or combined in anyorder. Further, each of the methods (or embodiments), an encoder, and adecoder may be implemented by processing circuitry (e.g., one or moreprocessors or one or more integrated circuits). In one example, the oneor more processors execute a program that is stored in a non-transitorycomputer-readable medium. Embodiments in the disclosure may be appliedto a luma block or a chroma block.

The techniques described above, can be implemented as computer softwareusing computer-readable instructions and physically stored in one ormore computer-readable media. For example, FIG. 17 shows a computersystem (1700) suitable for implementing certain embodiments of thedisclosed subject matter.

The computer software can be coded using any suitable machine code orcomputer language, that may be subject to assembly, compilation,linking, or like mechanisms to create code comprising instructions thatcan be executed directly, or through interpretation, micro-codeexecution, and the like, by one or more computer central processingunits (CPUs), Graphics Processing Units (GPUs), and the like.

The instructions can be executed on various types of computers orcomponents thereof, including, for example, personal computers, tabletcomputers, servers, smartphones, gaming devices, internet of thingsdevices, and the like.

The components shown in FIG. 17 for computer system (1700) are exemplaryin nature and are not intended to suggest any limitation as to the scopeof use or functionality of the computer software implementingembodiments of the present disclosure. Neither should the configurationof components be interpreted as having any dependency or requirementrelating to any one or combination of components illustrated in theexemplary embodiment of a computer system (1700).

Computer system (1700) may include certain human interface inputdevices. Such a human interface input device may be responsive to inputby one or more human users through, for example, tactile input (such as:keystrokes, swipes, data glove movements), audio input (such as: voice,clapping), visual input (such as: gestures), olfactory input (notdepicted). The human interface devices can also be used to capturecertain media not necessarily directly related to conscious input by ahuman, such as audio (such as: speech, music, ambient sound), images(such as: scanned images, photographic images obtain from a still imagecamera), video (such as two-dimensional video, three-dimensional videoincluding stereoscopic video).

Input human interface devices may include one or more of (only one ofeach depicted): keyboard (1701), mouse (1702), trackpad (1703), touchscreen (1710), data-glove (not shown), joystick (1705), microphone(1706), scanner (1707), camera (1708).

Computer system (1700) may also include certain human interface outputdevices. Such human interface output devices may be stimulating thesenses of one or more human users through, for example, tactile output,sound, light, and smell/taste. Such human interface output devices mayinclude tactile output devices (for example tactile feedback by thetouch-screen (1710), data-glove (not shown), or joystick (1705), butthere can also be tactile feedback devices that do not serve as inputdevices), audio output devices (such as: speakers (1709), headphones(not depicted)), visual output devices (such as screens (1710) toinclude CRT screens, LCD screens, plasma screens, OLED screens, eachwith or without touch-screen input capability, each with or withouttactile feedback capability—some of which may be capable to output twodimensional visual output or more than three dimensional output throughmeans such as stereographic output; virtual-reality glasses (notdepicted), holographic displays and smoke tanks (not depicted)), andprinters (not depicted).

Computer system (1700) can also include human accessible storage devicesand their associated media such as optical media including CD/DVD ROM/RW(1720) with CD/DVD or the like media (1721), thumb-drive (1722),removable hard drive or solid state drive (1723), legacy magnetic mediasuch as tape and floppy disc (not depicted), specialized ROM/ASIC/PLDbased devices such as security dongles (not depicted), and the like.

Those skilled in the art should also understand that term “computerreadable media” as used in connection with the presently disclosedsubject matter does not encompass transmission media, carrier waves, orother transitory signals.

Computer system (1700) can also include an interface (1754) to one ormore communication networks (1755). Networks can for example bewireless, wireline, optical. Networks can further be local, wide-area,metropolitan, vehicular and industrial, real-time, delay-tolerant, andso on. Examples of networks include local area networks such asEthernet, wireless LANs, cellular networks to include GSM, 3G, 4G, 5G,LTE and the like, TV wireline or wireless wide area digital networks toinclude cable TV, satellite TV, and terrestrial broadcast TV, vehicularand industrial to include CAN bus, and so forth. Certain networkscommonly require external network interface adapters that attached tocertain general-purpose data ports or peripheral buses (1749) (such as,for example USB ports of the computer system (1700)); others arecommonly integrated into the core of the computer system (1700) byattachment to a system bus as described below (for example Ethernetinterface into a PC computer system or cellular network interface into asmartphone computer system). Using any of these networks, computersystem (1700) can communicate with other entities. Such communicationcan be uni-directional, receive only (for example, broadcast TV),uni-directional send-only (for example CANbus to certain CANbusdevices), or bi-directional, for example to other computer systems usinglocal or wide area digital networks. Certain protocols and protocolstacks can be used on each of those networks and network interfaces asdescribed above.

Aforementioned human interface devices, human-accessible storagedevices, and network interfaces can be attached to a core (1740) of thecomputer system (1700).

The core (1740) can include one or more Central Processing Units (CPU)(1741), Graphics Processing Units (GPU) (1742), specialized programmableprocessing units in the form of Field Programmable Gate Areas (FPGA)(1743), hardware accelerators for certain tasks (1744), graphicsadapters (1750), and so forth. These devices, along with Read-onlymemory (ROM) (1745), Random-access memory (1746), internal mass storagesuch as internal non-user accessible hard drives, SSDs, and the like(1747), may be connected through a system bus (1748). In some computersystems, the system bus (1748) can be accessible in the form of one ormore physical plugs to enable extensions by additional CPUs, GPU, andthe like. The peripheral devices can be attached either directly to thecore's system bus (1748), or through a peripheral bus (1749). In anexample, the screen (1710) can be connected to the graphics adapter(1750). Architectures for a peripheral bus include PCI, USB, and thelike.

CPUs (1741), GPUs (1742), FPGAs (1743), and accelerators (1744) canexecute certain instructions that, in combination, can make up theaforementioned computer code. That computer code can be stored in ROM(1745) or RAM (1746). Transitional data can also be stored in RAM(1746), whereas permanent data can be stored for example, in theinternal mass storage (1747). Fast storage and retrieve to any of thememory devices can be enabled through the use of cache memory, that canbe closely associated with one or more CPU (1741), GPU (1742), massstorage (1747), ROM (1745), RAM (1746), and the like.

The computer readable media can have computer code thereon forperforming various computer-implemented operations. The media andcomputer code can be those specially designed and constructed for thepurposes of the present disclosure, or they can be of the kind wellknown and available to those having skill in the computer software arts.

As a non-limiting example, the computer system having architecture(1700), and specifically the core (1740) can provide functionality as aresult of processor(s) (including CPUs, GPUs, FPGA, accelerators, andthe like) executing software embodied in one or more tangible,computer-readable media. Such computer-readable media can be mediaassociated with user-accessible mass storage as introduced above, aswell as certain storage of the core (1740) that are of non-transitorynature, such as core-internal mass storage (1747) or ROM (1745). Thesoftware implementing various embodiments of the present disclosure canbe stored in such devices and executed by core (1740). Acomputer-readable medium can include one or more memory devices orchips, according to particular needs. The software can cause the core(1740) and specifically the processors therein (including CPU, GPU,FPGA, and the like) to execute particular processes or particular partsof particular processes described herein, including defining datastructures stored in RAM (1746) and modifying such data structuresaccording to the processes defined by the software. In addition or as analternative, the computer system can provide functionality as a resultof logic hardwired or otherwise embodied in a circuit (for example:accelerator (1744)), which can operate in place of or together withsoftware to execute particular processes or particular parts ofparticular processes described herein. Reference to software canencompass logic, and vice versa, where appropriate. Reference to acomputer-readable media can encompass a circuit (such as an integratedcircuit (IC)) storing software for execution, a circuit embodying logicfor execution, or both, where appropriate. The present disclosureencompasses any suitable combination of hardware and software.

While this disclosure has described several exemplary embodiments, thereare alterations, permutations, and various substitute equivalents, whichfall within the scope of the disclosure. It will thus be appreciatedthat those skilled in the art will be able to devise numerous systemsand methods which, although not explicitly shown or described herein,embody the principles of the disclosure and are thus within the spiritand scope thereof.

APPENDIX A: ACRONYMS

-   -   JEM: joint exploration model    -   VVC: versatile video coding    -   BMS: benchmark set    -   MV: Motion Vector    -   HEVC: High Efficiency Video Coding    -   SEI: Supplementary Enhancement Information    -   VUL Video Usability Information    -   GOPs: Groups of Pictures    -   TUs: Transform Units,    -   PUs: Prediction Units    -   CTUs: Coding Tree Units    -   CTBs: Coding Tree Blocks    -   PBs: Prediction Blocks    -   HRD: Hypothetical Reference Decoder    -   SNR: Signal Noise Ratio    -   CPUs: Central Processing Units    -   GPUs: Graphics Processing Units    -   CRT: Cathode Ray Tube    -   LCD: Liquid-Crystal Display    -   OLED: Organic Light-Emitting Diode    -   CD: Compact Disc    -   DVD: Digital Video Disc    -   ROM: Read-Only Memory    -   RAM: Random Access Memory    -   ASIC: Application-Specific Integrated Circuit    -   PLD: Programmable Logic Device    -   LAN: Local Area Network    -   GSM: Global System for Mobile communications    -   LTE: Long-Term Evolution    -   CANBus: Controller Area Network Bus    -   USB: Universal Serial Bus    -   PCI: Peripheral Component Interconnect    -   FPGA: Field Programmable Gate Areas    -   SSD: solid-state drive    -   IC: Integrated Circuit    -   HDR: high dynamic range    -   SDR: standard dynamic range    -   JVET: Joint Video Exploration Team    -   MPM: most probable mode    -   WAIP: Wide-Angle Intra Prediction    -   CU: Coding Unit    -   PU: Prediction Unit    -   TU: Transform Unit    -   CTU: Coding Tree Unit    -   PDPC: Position Dependent Prediction Combination    -   ISP: Intra Sub-Partitions    -   SPS: Sequence Parameter Setting    -   PPS: Picture Parameter Set    -   APS: Adaptation Parameter Set    -   VPS: Video Parameter Set    -   DPS: Decoding Parameter Set    -   ALF: Adaptive Loop Filter    -   SAO: Sample Adaptive Offset    -   CC-ALF: Cross-Component Adaptive Loop Filter    -   CDEF: Constrained Directional Enhancement Filter    -   CCSO: Cross-Component Sample Offset    -   LSO: Local Sample Offset    -   LR: Loop Restoration Filter    -   AV1: AOMedia Video 1    -   AV2: AOMedia Video 2

What is claimed is:
 1. A method for processing video information,comprising: identifying a plurality of transform kernels, wherein: eachof the plurality of transform kernels comprises a set of basis vectorsfrom low to high frequencies; N high-frequency basis vectors of two ormore of the plurality of transform kernels are shared, N being apositive integer; and low-frequency basis vectors of the two or more ofthe plurality of the transform kernels other than the N high-frequencybasis vectors are individualized; extracting a data block from a videobitstream; selecting a transform kernel from the plurality of transformkernels based on information associated with the data block; andapplying the transform kernel to at least a portion of the data block togenerate a transformed block.
 2. The method of claim 1, wherein theplurality of transform kernels are pre-trained offline.
 3. The method ofclaim 2, wherein the plurality of transform kernels are jointly trainedoffline to determine the N high-frequency basis vector being shared. 4.The method of claim 1, wherein the N high-frequency basis vectorscomprise basis vectors with frequencies higher than a predeterminedthreshold frequency.
 5. The method of claim 4, wherein the plurality oftransform kernels and the predetermined threshold frequency arepre-trained offline.
 6. The method of claim 1, wherein: the plurality oftransform kernels comprise secondary transform kernels applicable totransforming primary transform coefficients; and the data blockcomprises an array of primary transform coefficients.
 7. The method ofclaim 1, wherein: the two or more of the plurality of transform kernelssharing the N high-frequency basis vectors correspond to a same one of aplurality of intra-picture prediction modes; and all transform kernelsamong the plurality of the transform kernels assigned to the same one ofthe plurality of intra-picture prediction modes share the Nhigh-frequency basis vectors with other low-frequency basis vectorsbeing individualized.
 8. The method of claim 1, wherein the two or moreof the plurality of transform kernels sharing the N high-frequency basisvectors are assigned to two or more different intra-picture predictionmodes.
 9. The method of claim 1, wherein: the plurality of transformkernels are secondary transform kernels; and the two or more of theplurality of transform kernels sharing the N high-frequency basis vectorare configured to transform primary transform coefficients generatedfrom primary transforms having a same transform type.
 10. The method ofclaim 1, wherein N is an integer power of
 2. 11. The method of claim 10,wherein N is smaller than a predefined upper bound.
 12. The method ofclaim 1, wherein N depends on a transform size.
 13. The method of claim1, wherein the plurality of transform kernels are secondary lowfrequency non-separable transform (LFNST) kernels.
 14. The method ofclaim 1, wherein the plurality of transform kernels are configured forintra secondary transform (IST).
 15. The method of claim 1, wherein theplurality of transform kernels are configured for line graph transform(LGT).
 16. A device for processing video information, comprising acircuitry configured to: identify a plurality of transform kernels,wherein: each of the plurality of transform kernels comprises a set ofbasis vectors from low to high frequencies; N high-frequency basisvectors of two or more of the plurality of transform kernels are shared,N being a positive integer; and low-frequency basis vectors of the twoor more of the plurality of the transform kernels other than the Nhigh-frequency basis vectors are individualized; extract a data blockfrom a video bitstream; select a transform kernel from the plurality oftransform kernels based on information associated with the data block;and apply the transform kernel to at least a portion of the data blockto generate a transformed block.
 17. The device of claim 16, wherein:the plurality of transform kernels comprise secondary transform kernelsapplicable to transforming primary transform coefficients; and the datablock comprises an array of primary transform coefficients.
 18. Thedevice of claim 16, wherein: the two or more of the plurality oftransform kernels sharing the N high-frequency basis vectors correspondto a same one of a plurality of intra-picture prediction modes; and alltransform kernels among the plurality of the transform kernels assignedto the same one of the plurality of intra-picture prediction modes sharethe N high-frequency basis vectors with other low-frequency basisvectors being individualized.
 19. The device of claim 16, wherein thetwo or more of the plurality of transform kernels sharing the Nhigh-frequency basis vectors are assigned to two or more differentintra-picture prediction modes.
 20. The device of claim 16, wherein: theplurality of transform kernels are secondary transform kernels; and thetwo or more of the plurality of transform kernels sharing the Nhigh-frequency basis vector are configured to transform primarytransform coefficients generated from primary transforms having a sametransform type.